Conformal predictive decision making. / Vovk, Vladimir; Bendtsen, Claus.

Proceedings of Machine Learning Research. ed. / Alex Gammerman; Vladimir Vovk; Zhiyuan Luo; Evgueni Smirnov; Ralf Peeters. Vol. 91 2018. p. 52-62.

Research output: Chapter in Book/Report/Conference proceedingChapter

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Abstract

This note explains how conformal predictive distributions can be used for the purpose of decision making. Namely, a major limitation of conformal predictive distributions is that, at this time, they are only applicable to regression problems, where the label is a real number; however, this does not prevent them from being used in a general problem of decision making. The resulting methodology of conformal predictive decision making is illustrated on a small benchmark data set. Our main theoretical observation is that there exists an asymptotically efficient predictive decision-making system which can be obtained by using our methodology (and therefore, satisfying the standard property of validity).
Original languageEnglish
Title of host publicationProceedings of Machine Learning Research
EditorsAlex Gammerman, Vladimir Vovk, Zhiyuan Luo, Evgueni Smirnov, Ralf Peeters
Pages52-62
Number of pages11
Volume91
StatePublished - Jun 2018
This open access research output is licenced under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.

ID: 29977518